叶敏超
sex
1
title
副教授
department
信息工程学院
college

college2

degree
博士
recruit":0,"firstDiscipline1
计算机科学与技术
secondaryDiscipline1

firstDiscipline2
电子信息
secondaryDiscipline2

executive

officePhone

mobilePhone
壹③柒柒柒④叁6⑤2捌
emailAddress
yeminchao(at)cjlu.edu.cn
businessAddress
赛博北楼312
individualResume
叶敏超，中国计量大学信息工程学院计算机科学与技术学科副教授。研究方向为高光谱图像处理，研究重点为高光谱图像分类和去噪。近年来主要研究高光谱图像的跨场景特征提取、特征选择、分类算法，以及图非负矩阵分解在高光谱图像中的应用。目前在研国家自然科学基金青年项目：基于特征子空间学习的跨场景异构高光谱图像分类。在高光谱图像处理方向的国际会议IEEE IGARSS、国际期刊IEEE Transactions on Geoscience and Remote Sensing、IEEE Journal of Selected Topics in Applied Earth Observations，以及机器学习方向期刊Neural　Computing　and　Applications上发表有学术论文。\r\r教育、工作经历：\r2006.9 - 2010.6 四川大学计算机学院 计算机科学与技术 本科\r2010.9 - 2016.3 浙江大学计算机学院 计算机科学与技术 博士（直接攻博）\r2016.6 - 至今 中国计量大学信息工程学院 计算机科学与技术 教师\r\r
researchTopic
国家自然科学基金青年项目 ** 基于特征子空间学习的跨场景异构高光谱图像分类 20万元\r
awards

researchProject
国家自然科学基金青年项目 ** 基于特征子空间学习的跨场景异构高光谱图像分类 20万元
publications
[1] Hong Chen, Minchao Ye, Ling Lei, et al. Semisupervised Dual-Dictionary Learning for Heterogeneous Transfer Learning on Cross-Scene Hyperspectral Images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020, 13: 3164-3178.\r[2] Minchao Ye, Chenxi Ji, Hong Chen, et al. Residual deep PCA-based feature extraction for hyperspectral image classification[J]. Neural Computing and Applications, 2019: 1-14.\r[3] Minchao Ye, Hong Chen, Chenxi Ji, et al. Spectral-Spatial Joint Noise Estimation for Hyperspectral Images[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 230-233.\r[4] Minchao Ye, Chenxi Ji, Hong Chen, et al. Feature selection for cross-scene hyperspectral image classification using cross-domain ReliefF[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2019: **.\r[5] Hong Chen, Minchao Ye, Huijuan Lu, et al. Dual Dictionary Learning for Mining a Unified Feature Subspace between Different Hyperspectral Image Scenes[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 1096-1099.\r[6] Chenxi Ji, Minchao Ye, Huijuan Lu, et al. Feature Extraction of Hyperspectral Imagery Based on Deep NMF[C]//IEEE International Geoscience and Remote Sensing Symposium. 2019: 1092-1095.\r[7] Minchao Ye, Yongqiu Xu, Huijuan Lu, et al. Cross-Scene Feature Selection for Hyperspectral Images Based on Cross-Domain Information Gain[C]//IEEE International Geoscience and Remote Sensing Symposium. 2018: 4764-4767.\r[8] Minchao Ye, Yuntao Qian, Jun Zhou, et al. Dictionary Learning-Based Feature-Level Domain Adaptation for Cross-Scene Hyperspectral Image Classification[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(3):1544-1562.\r[9] Minchao Ye, Wenbin Zheng, Huijuan Lu, et al. Cross-scene hyperspectral image classification based on DWT and manifold-constrained subspace learning[J]. International Journal of Wavelets, Multiresolution and Information Processing, 2017, 15(06): **.\r[10] Minchao Ye, Yuntao Qian, Jun Zhou. Multitask sparse nonnegative matrix factorization for joint spectral-spatial hyperspectral imagery denoising[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(5): 2621-2639.
others
软件著作权4项
correlation
researchDirection1
高光谱图像处理
researchDirection2
机器学习
researchDirection3
模式识别
researchDirection4